Jørgen Brandt

TransCom model simulations of hourly atmospheric CO2: Analysis of synoptic-scale variations for the period 2002-2003

The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.

TransCom model simulations of hourly atmospheric CO2 : experimental overview and diurnal cycle results for 2002

[1] A forward atmospheric transport modeling experiment has been coordinated by the TransCom group to investigate synoptic and diurnal variations in CO2. Model simulations were run for biospheric, fossil, and air-sea exchange of CO2 and for SF6 and radon for 2000-2003. Twenty-five models or model variants participated in the comparison. Hourly concentration time series were submitted for 280 sites along with vertical profiles, fluxes, and meteorological variables at 100 sites. The submitted results have been analyzed for diurnal variations and are compared with observed CO2 in 2002. Mean summer diurnal cycles vary widely in amplitude across models. The choice of sampling location and model level account for part of the spread suggesting that representation errors in these types of models are potentially large. Despite the model spread, most models simulate the relative variation in diurnal amplitude between sites reasonably well. The modeled diurnal amplitude only shows a weak relationship with vertical resolution across models; differences in near-surface transport simulation appear to play a major role. Examples are also presented where there is evidence that the models show useful skill in simulating seasonal and synoptic changes in diurnal amplitude.

The Long Range Transport of Birch (Betula) Pollen from Poland and Germany Causes Significant Pre-season Concentrations in Denmark

Background Birch pollen is highly allergic and has the potential for episodically long‐range transport. Such episodes will in general occur out of the main pollen season. During this time, allergy patients are unprotected and high pollen concentrations will therefore have a full allergenic impact.

Operational air pollution forecasts from European to local scale

Abstract A new operational air pollution forecast system, THOR, has been developed at the National Environmental Research Institute, Denmark. The integrated system consists of a series of air pollution models, covering a wide range of scales (from European scale to street scale in cities) and applications. The system is designed to automatically produce 3 days air pollution forecasts of the most important air pollution species on different scales on a continuous basis. The various models, the coupling/integration and the configuration of the models, the visualizations and the real-time performance on fast workstations with parallel architecture will be described. Some examples of model results and validations on street level are presented.

The Pannonian plain as a source of Ambrosia pollen in the Balkans

This study aims to find likely sources of Ambrosia pollen recorded during 2007 at five pollen-monitoring sites in central Europe: Novi Sad, Ruma, Negotin and Nis (Serbia) and Skopje (Macedonia). Ambrosia plants start flowering early in the morning and so Ambrosia pollen grains recorded during the day are likely to be from a local source. Conversely, Ambrosia pollen grains recorded at night or very early in the morning may have arrived via long-range transport. Ambrosia pollen counts were analysed in an attempt to find possible sources of the pollen and to identify Ambrosia pollen episodes suitable for further investigation using back-trajectory analysis. Diurnal variations and the magnitude of Ambrosia pollen counts during the 2007 Ambrosia pollen season showed that Novi Sad and Ruma (Pannonian Plain) and to a lesser degree Negotin (Balkans) were located near to sources of Ambrosia pollen. Mean bi-hourly Ambrosia pollen concentrations peaked during the middle of the day, and concentrations at these sites were notably higher than at Nis and Skopje. Three episodes were selected for further analysis using back-trajectory analysis. Back-trajectories showed that air masses brought Ambrosia pollen from the north to Nis and, on one occasion, to Skopje (Balkans) during the night and early morning after passing to the east of Novi Sad and Ruma during the previous day. The results of this study identified the southern part of the Pannonian Plain around Novi Sad and Ruma as being a potential source region for Ambrosia pollen recorded at Nis and Skopje in the Balkans.

Comparison of five eulerian air pollution forecasting systems for the summer of 1999 using the German ozone monitoring data

Eulerian state-of-the-art air pollution forecasting systems on the European scale are operated routinely by several countries in Europe. DWD and FUB, both Germany, NERI, Denmark, NILU, Norway, and SMHI, Sweden, operate some of these systems. To apply such modeling systems, e.g. for regulatory purposes according to new EU directives, an evaluation and comparison of the model systems is fundamental in order to assess their reliability. One step in this direction is presented in this study: The model forecasts from all five systems have been compared to measurements of ground level ozone in Germany. The outstanding point in this investigation is the availability of a huge amount of data – from forecasts by the different model systems and from observations. This allows for a thorough interpretation of the findings and assures the significance of the observed features. Data from more than 300 measurement stations for a 5-month period (May–September 1999) of the German monitoring networks have been used in this comparison. Different spatial and temporal statistical parameters were applied in the evaluation. Generally, it was found that the most comprehensive models gave the best results. However, the less comprehensive and computational cheaper models also produced good results. The extensive comparison made it possible to point out weak points in the different models and to describe the individual model behavior for a full summer period in a climatological sense. The comparison also gave valuable information for an assessment of individual measurement stations and complete monitoring networks in terms of the representativeness of the observation data.

Studying cumulative ozone exposures in Europe during a 7‐year period

Ozone is one of the most harmful pollutants in the troposphere. High ozone concentrations can damage plants, animals and humans. The damaging effects depend on the magnitude of a critical level of a special parameter, the cumulative ozone exposure. This is why cumulative ozone exposures must be carefully studied. It is important to determine the relation- ships between relevant emissions (NOx emissions, human-made VOC emissions, and/or a combination of NOx emissions and human-made VOC emissions) and cumulative ozone exposures. All these issues are discussed in this paper. Meteorological data from seven consecutive years, from 1989 to 1995, have been used in the experiments with different scenarios for varying the emissions (the NOx emissions, the human-made VOC emissions, as well as both the NOx emissions and the human-made VOC emissions). The particular air pollution model used in this study is the Danish Eulerian Model. Several hundred runs with different input data (meteorological data and/or emission data) have been performed. Advanced visualization techniques are used to interpret the large amount of digital data collected in these runs and to show clearly different trends and relationships that are normally hidden behind millions and millions of numbers. The model results were compared with measurements taken at more than 80 stations located in different European countries. The experiments indicate that it is sufficient to carry out computations over 5 consecutive years in order to eliminate the influence of extreme meteorological conditions (very warm or very cold summer months) on the cumulative ozone exposures, while this effect is clearly seen if less than 5 years are used in the experiments. It is shown that the relationship between the emissions (NOand/or human- made VOC emissions) and the cumulative ozone exposures is in general nonlinear. Finally, it is illustrated that the critical values for ozone exposures are exceeded in most of Europe (in many areas by more than 7 times).

Investigating the sources of synoptic variability in atmospheric CO2 measurements over the Northern Hemisphere continents: a regional model study

Continuous measurements of atmospheric CO2 over the continents are potentially powerful tools for understanding regional carbon budgets, but our limited understanding of the processes driving the high-frequency variability in these measurements makes interpretation difficult. In this paper we examine the synoptic variability (⊼days) of surface CO2 concentrations in four continental records from Europe and North America. Three source functions corresponding to the ocean, land biosphere and anthropogenic sources and sinks for CO2 have been implemented in a regional atmospheric transport model. In previous carbon studies, monthly biospheric fluxes have typically been used, but here high spatiotemporal (daily, 1¼×1¼) resolution biospheric fluxes are obtained from the NCAR Land Surface Model (lsm). A high-pass filter is used to remove atmospheric variability on time scales longer than 2 months, and the resulting simulated concentration fields replicates reasonably well the magnitude and seasonality of the synoptic variability across the four observation sites. The phasing of many of the individual events are also captured, indicating that the physical and biogeochemical dynamics driving the model variability likely resemble those in nature.The observations and model results show pronounced summer maxima in the synoptic CO2 concentration variability at the two stations located in North America, while a slightly different seasonality with high variability throughout fall and winter is observed at the European sites. The mechanisms driving these patterns are studied and discussed based on correlations between the concentration anomalies and the driving atmospheric physical variables and surfaces fluxes in the simulations. During the summer, the synoptic variability over the continents has a significant contribution from variations in regional net primary production, which in turn is modulated by regional, synoptic temperature variability. In winter the synoptic variability is partitioned about equally between biospheric and anthropogenic CO2 and is mainly driven by local vertical mixing and synoptic variations in atmospheric circulation working on the large-scale atmospheric gradient. This study highlights the importance for future modeling work of improved high temporal resolution (at least daily) surface biosphere, oceanic and anthropogenic flux estimates as well as high vertical and horizontal spatiotemporal resolution of the driving meteorology.

Zero-Knowledge Authentication Scheme with Secret Key Exchange

Abstract. In this paper we formally define proof systems for functions and develop an example of such a proof with a constant number of rounds, which we modify (at no extra communication cost) into an identification scheme with secret key exchange for subsequent conventional encryption. Implemented on a standard 32-bit chip or similar, the whole protocol, which involves mutual identification of two users, exchange of a random common secret key, and verification of certificates for the public keys (RSA, 512 bits) takes less than 3/4 second.

Testing the importance of accurate meteorological input fields and parameterizations in atmospheric transport modelling using dream - validation against ETEX-1

A tracer model, the DREAM, which is based on a combination of a near-range Lagrangian model and a long-range Eulerian model, has been developed. The meteorological meso-scale model, MM5V1, is implemented as a meteorological driver for the tracer model. The model system is used for studying transport and dispersion of air pollutants caused by a single but strong source as, e.g. an accidental release from a nuclear power plant. The model system including the coupling of the Lagrangian model with the Eulerian model are described. Various simple and comprehensive parameterizations of the mixing height, the vertical dispersion, and different meterological input data have been implemented in the combined tracer model, and the model results have been validated against measurements from the ETEX-1 release. Several different statistical parameters have been used to estimate the differences between the parameterizations and meterological input data in order to find the best performing solution.